BME100 f2014:Group5 L6

BME 100 Fall 2014	Home People Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3 Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6 Course Logistics For Instructors Photos Wiki Editing Help
OUR COMPANY Megan Danforth Jad Jazzar Christopher Rojas Keaton Sorenson Sahar Mohamed Zahra Khuraidah LAB 6 WRITE-UP Bayesian Statistics Overview of the Original Diagnosis System DNA was amplified and analyzed in a open PCR machine from 68 different patients. There were 34 groups of six students each that analyzed two patients for a disease-associated SNP. After the DNA was amplified, three samples were made from each patient so that each group had six samples to test for the disease-associated SNP. The amplified DNA was mixed with SYBR green and analyzed through image analysis of drops in a fluorimeter. In order to limit error in the data analysis, groups only needed to test two patients. Each patient had three tests done with the fluorimeter so that our results were more accurate. In addition, error was reduced because of accurate imageJ analysis in which the oval perfectly matched up with the picture. All the pictures were taken with the same settings and were all focused. There were three pictures per drop as well making 9 total pictures to analyze per patient and 18 total per group. If everything went perfectly in the lab, the PCR conclusion and whether or not the patient had the disease should match up. If the PCR conclusion was “yes”, then the disease would have been present. If the PCR conclusion was “no”, then the disease would not be present. However, this is not the case for the class data as a whole. There were some inconclusive data sets from the PCR, and thus no data was able to support a claim about disease presence. There should be results for all 68 patients. 30 patients had a positive result, 24 patients had a negative result, 8 were inconclusive, and 6 tests failed to provide any data or were not tested at all. Overall, the PCR’s conducted only correctly identified 10 out of 23 patients that actually had the disease 12 out of 45 patients that did not have the disease. What Bayes Statistics Imply about This Diagnostic Approach Computer-Aided Design TinkerCAD TinkerCAD is a web based design software. It comes with preprogrammed shapes and teaches you how to use the program with ease. The group imported shapes from the original PCR machine design and built the original device. The tools on TinkerCAD were used to make sure the machine was of correct size and shape. Our Design The group decided to add a second chamber to the machine. This change to the design allows for twice the data collection of the original device. The design was choose in order to allow for the machine to be more efficient. Feature 1: Consumables Kit Feature 2: Hardware - PCR Machine & Fluorimeter Using the fluorimeter was a complicated process with the many different variables that could affect the results. One of the bad things to use the fluorimter is that we cannot stand up the phone to take a picture for the drop, so this make a bad result. Other thing that we have hard time on it that is the distance from the camera and the fluorimeter, so we lost a lot of time to sand up the phone and modifying the distance between the camera and fluorimeter. The main focus of our designed PCR machine set would be portability, meaning that make the stand have two screws in each said to stand up the phone in a straight side and we can change this size depends on the phone’s style. The second improvement is to have other screw in the back of our PCR machine to move the drop in the same way of the camera to have good results. Regarding the fluorimeter, the entire device would be one apparatus, with these changes, which make the PCS a little bit expansive but having best results.